Interior design for configurable spaces, including passenger vehicles, such as airplanes, buses, subway and train cars, requires adherence to numerous standards and rules. For example, in the United States, the Federal Aviation Administration imposes restrictions on commercial airliners regarding the number of doors, distance between doors and seats or other landmarks, and width of aisles. Additionally, customers or users of the passenger vehicles submit their own requirements regarding distance between seats and other landmarks, in different classes of seating. In addition to specific rules, an overriding concern of manufacturers and purchasers of passenger vehicles is often the optimization of the available interior space to fit the most possible passengers, given the constraints of government, industry, and/or customer rules.
Current interior configuration modeling systems use a manually intensive process. Systems are able to model an interior using exact coordinates of each landmark, without regard for the location of each landmark relative to the other landmarks. This manually intensive process has trouble keeping pace with the rapid change in overall aircraft configuration. For example, if a person charged with the configuration of interiors of passenger vehicles (an “interior configurator”) adds a landmark to the configuration, current interior configuration models are unable to shift seats or other landmarks in an efficient way, while also taking into account the constraints of rules imposed by governments, industry standards, and/or customers. Thus, the configurator would have to manually adjust the configuration of the interior to meet rules and standards.
Also, current interior configuration models do not automatically insure optimal seat and landmark locations, allowing for the largest number of seats possible under current constraints. Decisions made using current configuration models are based on limited arrangement data requiring an educated guess as to whether a configuration is optimized. Because the current tools require manual entry of coordinate data for landmarks and seats, the current tool requires constant regular use and a high level of expertise in order to be proficient at configuring and designing interiors. Finally, current tools allow for only manual extraction of internal configuration data, which is of limited utility for downstream processes such as assembly or maintenance.
Accordingly, it would be desirable to use a knowledge-based approach to automate the interior development process. Also, it would be desirable to store configuration data in a manner so that it is accessible to downstream users.
When an airplane is designed for an airline, one of the decisions the airline customer needs to make is what commodities, accessories, spatial walking room, etc., is required for their unique airplane in the passenger compartment where passengers board and travel. This passenger compartment in design terms is called a LOPA, Layout Passenger Accommodations, because it accommodates all the passenger requirements as they sit and travel in the airplane.
The LOPA includes physical commodities, such as galleys, lavatories, closets and stowage bins, etc. Also included in the LOPA are non-physical objects such as walking areas (in cross aisles and passageways), clearance areas for doors, areas where flight attendants sit, and many other areas. There is also space defined where an object may occupy if the airplane were to drop or stop suddenly. Examples of this space is a head strike zone where the passenger's head would travel if projected forward, or seat deflection space, where the seat may move slightly forward. Sometimes spatial areas are required if in front of a passenger seat, for example, where other times it is not required, such as in front of a panel, or partition. Deciding and designing the placement of all these objects, commodities and spatial areas and zones, is a detailed and time consuming task.
A CATIA 3D CAD/CAM (computer aided design/computer aided manufacturing) prototype is used to validate separation/collision in specific cases to validate clearances. Real life prototypes are created out of materials (cardboard, seats . . . ) to imitate the space required between objects. A tape measure is used to measure the distance, or humans are used to validate the clearances. However, the above manual methods are used, but only where validation is required. These manual methods are not very accurate, and are prone to wasted space or even error.
There are disadvantages and limitations of current solutions, in that current processes limit the placement in a 2D (two dimensional) space. Further, related solutions are not able to calculate accurate collisions in all 3D (three dimensional) space directions. Current methods using programmed tools lend to timely and inaccurate measurement calculations between objects. Current method using prototypes are very time dependent, crude and are not always accurate. It is easy to miss separation requirements in detailed object profiles including shape.
Therefore, the current solutions are not able to provide a reasonable solution as shown above.